Title :
Adaptive order selection with aid of genetic algorithm
Author :
Ikoma, Norikazu ; Maeda, Hiroshi
Author_Institution :
Dept. of Comput. Sci., Kyushu Inst. of Technol., Kitakyushu, Japan
Abstract :
A method to estimate a nonstationary power spectrum with adaptive selection of autoregressive order is proposed. Time-varying PARCOR (partial autocorrelation coefficient) and AR (autoregressive) order are estimated from time series data. The data are assumed to be observations of vibration that contain abrupt change of spectrum due to arrivals of different signal, structural changes of vibrating object, etc. The model that consists of an autoregressive model with time-varying PARCORs and time-varying order is used. The time-varying PARCORs are estimated by a Monte Carlo filter, and the time-varying order is estimated by genetic algorithm. An application to analysis of seismic wave data is reported.
Keywords :
Monte Carlo methods; autoregressive processes; filtering theory; genetic algorithms; parameter estimation; spectral analysis; time series; Monte Carlo filter; adaptive order selection; autoregressive order; nonstationary power spectrum; seismic wave data; time-varying order; time-varying partial autocorrelation coefficient; vibrating object; Computer science; Filters; Fourier transforms; Genetic algorithms; Monte Carlo methods; Power engineering and energy; Seismic waves; Spectral analysis; State estimation; Time series analysis;
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
Print_ISBN :
0-7803-5406-0
DOI :
10.1109/FUZZY.1999.790178
